Image-Only Detection.
Following the previous work  [1]}, we first explore whether we can train a simple binary ML classifier to differentiate generated images from real images.
As we mentioned that the universal detection should be agnostic to diffusion algorithms and datasets.
Thus, we only choose the generated images of one diffusion model trained on one certain dataset, as well as the corresponding real images to build the binary classifier.
